Feasibility studies

Forward modelling of gravity and height based on subsurface models. Data on an observation grid is simulated.
Quad Geometrics

Input data (which a study usually is based on)

  • Geometry of the reservoir or subsurface target
  • Rock properties, such as porosity, fluids, pressures, and their dynamic (time-lapse) changes. Often reservoir flow models contains all required information.
  • Rock stiffness, uniaxial or triaxial, rock or pore compressibility
  • Quantification of model uncertainties or multiple subsurface models
  • Seafloor or surface topography. Geotechnical properties for the foundation of measurement platforms
  • Station layout, or multiple layouts
  • Cost of different components of data aquisition

Forward modelling from subsurface models

  • Calculate geometry of reservoir mass changes from the property model(s). Gravity forward modelling to the surface station grid(s) using Newtons law.
  • Calculate geometry of reservoir heights from the property model(s), usually pore pressure. Deformation forward modelling to the surface station grid(s) using the Geertsma approximation.

Simulating surveys

  • Select station grid(s), if not given initially
  • Add noise with realistic level and properties
  • Simulate noisy data with sequence of measurements, drift errors and other correlated noise components
  • Process the simulated data
  • Match with reservoir models or invert for reservoir properties
  • Estimate uncertainties based on mis-matches or inverted differences from initial model
  • Cost estimates for various station grids and survey layouts

Cost-benefit analysis

station coverage density (blue line) and indicative value of data (orange line). The largest separation of the curves, at 500-600 m spacing, may give the highest net value. from eiken and zumberge (2019).
  • Cost estimates for various station grids and survey layouts
  • Precision of final results for various costs
  • Value of data for different scenarios
  • Cost-benefit analysis